IEEE WACV 2021 – Paper accepted

Our paper entitled “Illumination Normalization by Partially Impossible Encoder-Decoder Cost Function” has been accepted for publication at IEEE Winter Conference on Applications of Computer Vision (WACV 2021). We present an image normalization method based on a new strategy for the cost function formulation of encoder-decoder networks to average out all the unimportant information in the input images, in particular, to remove illumination changes and environmental features. Together with our proposed method, we release a synthetic dataset – an extension of SVIRO – of sceneries from three different passenger compartments where each scenery is rendered under ten different illumination and environmental.

IEEE WACV 2020 – Paper accepted

Our paper entitled “SVIRO: Synthetic Vehicle Interior Rear Seat Occupancy Dataset and Benchmark” has been accepted for publication at IEEE Winter Conference on Applications of Computer Vision (WACV 2020). This paper gives a detailed overview about SVIRO, some baseline investigations to highlight the challenging conditions of our dataset and some results on real images to show that insights on SVIRO are transferable to real images. This launches the release of the dataset and start of the public benchmark.